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POCUS: mining genomic sequence annotation to predict disease genes.

Frances S Turner·Daniel R Clutterbuck·Colin A M Semple
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Abstract

Here we present POCUS (prioritization of candidate genes using statistics), a novel computational approach to prioritize candidate disease genes that is based on over-representation of functional annotation between loci for the same disease. We show that POCUS can provide high (up to 81-fold) enrichment of real disease genes in the candidate-gene shortlists it produces compared with the original large sets of positional candidates. In contrast to existing methods, POCUS can also suggest counterintuitive candidates.

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Autistic DisorderCarrier ProteinsCell Adhesion Molecules, NeuronalComputational BiologyGenetic Predisposition to DiseaseHumansMembrane ProteinsMutationNerve Tissue ProteinsProbabilitySequence Analysis, DNAJournal ArticleResearch Support, Non-U.S. Gov't

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Frances S Turner, Daniel R Clutterbuck, Colin A M Semple. 2003-10-10. POCUS: mining genomic sequence annotation to predict disease genes.. https://doi.org/10.1186/gb-2003-4-11-r75

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